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Dear drs. Muthen, I am running a twolevel latent profile analysis in which the BIC seems to suggest relatively high numbers of classes on both levels. I am wondering if the existence of zero class counts for some combinations of within and between classes (e.g. zero persons assigned to the between 2/within 8 class) is unacceptable and implies misspecification - or does it simply mean that some level 2 classes have fewer level 1 classes occurring in them than others. All between- and within-level classes have persons assigned to them. |
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Having those empty cells is not a problem and should not hurt BIC. |
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Hi again, I want to regress distal outcomes on latent profiles at both levels. Is the procedure for doing this a straightforward extension of regressing a distal outcome on a latent categorical in a single-level model? More specifically; can I simply compare thresholds across within-level profiles and compare means across between-level profiles, as in the following? (distal_between is the aggregated counterpart of distal_within) ... VARIABLE: CATEGORICAL = distal_within ; WITHIN = ....... distal_within ; BETWEEN = ........cb distal_between ; ... MODEL: %WITHIN% %OVERALL% cw distal_within ON covariates ; %BETWEEN% %OVERALL% cw ON cb ; MODEL cw: %WITHIN% %cw#1% [distal_within$1] (t1); %cw#2% [distal_within$1] (t2); MODEL cb: %BETWEEN% %cw#1% [distal_between] (t3); %cw#2% [distal_between] (t4); MODEL CONSTRAINT: new(logOR_2_1) ; logOR_2_1 = t1-t2 ; new(OR2vs1) ; OR2vs1 = exp(t1-t2) ; MODEL TEST: t3=t4 ; |
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This looks correct. |
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